Hexagonal Binning
Chart overview
Hexagonal binning divides the 2D plane into a regular hexagonal grid and colours each cell by the number of data points it contains, creating a smooth density map that remains readable at very large sample sizes.
Key points
- Scientists in genomics, astrophysics, and imaging use it when standard scatter plots produce an uninformative black mass due to overplotting.
- The hexagonal geometry minimises binning artefacts compared to square grids and allows accurate perception of density gradients.
Example Visualization
Create This Chart Now
Generate publication-ready hexagonal binnings with AI in seconds. No coding required – just describe your data and let AI do the work.
View example prompt
"Create a hexagonal binning plot from my data. Choose an appropriate grid size, colour hexagons by point count using a sequential colormap, add a colorbar labelled with count or density, overlay marginal histograms if space permits, and format as a publication-quality figure."
How to create this chart in 30 seconds
Upload Data
Drag & drop your Excel or CSV file. Plotivy securely processes it in your browser.
AI Generation
Our AI analyzes your data and generates the Hexagonal Binning code automatically.
Customize & Export
Tweak the design with natural language, then export as high-res PNG, SVG or PDF.
Python Code Example
Console Output
Figure saved: plotivy-hexagonal-binning.png
Common Use Cases
- 1Visualising allele frequency distributions from genome-wide association studies with millions of SNPs
- 2Showing photometric magnitude versus colour index for stellar populations in large sky surveys
- 3Displaying the relationship between two biomarkers measured across thousands of patients
- 4Representing pixel intensity co-occurrence in multi-channel fluorescence microscopy data
Pro Tips
Adjust hexbin gridsize parameter to balance detail and smoothness for your sample size
Use a logarithmic colour scale when count values span several orders of magnitude
Overlay a contour line at key density percentiles to highlight the core data region
Remove empty hexagons by setting a minimum count threshold to reduce visual clutter
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.